• Annual Conference of KIPS
• /
• 2015.10a
• /
• pp.1289-1291
• /
• 2015

본 논문에서는 충치 환자의 진단을 위해 구강 영상에서 충치를 추출하는 방법을 제안한다. 먼저 구강은 붉은색을 띄고 치아는 흰색을 띈다는 특징이 있기 때문에, 구강 영상을 YCbCr 컬러모델로 변환한다. YCbCr 컬러모델에 임계치를 설정하여 붉은 영역을 검출해내고, 검출된 붉은 영역에 대해 이진화하여 치아 영역을 추출한다. 그 후, 모폴로지 기법을 이용하여 잡음 제거 및 치아의 빈 공간을 채운다. 치아 영역 추출 시 영상에 따라 치아 사이를 잇는 모서리 부분이 손실된 경우가 발생할 수 있기 때문에 치아 사이의 손실된 부분을 연결 한다. 치아 영역에 ART2 알고리즘을 적용하여 클러스터링하고 충치 후보 영역을 추출한다. 충치 후보 영역에 8방향 윤곽선 추적 기법을 적용하여 충치를 분석 및 추출한다. 실험 결과 81%의 추출 성공률을 보였고 다양한 형태의 충치를 효과적으로 추출할 수 있는 것을 확인하였다.

• Journal of the Korea Society of Computer and Information
• /
• v.18 no.8
• /
• pp.65-75
• /
• 2013

This paper proposes a method of tracking the hand region and detecting the fingertip using only depth images. In order to eliminate the influence of lighting conditions and obtain information quickly and stably, this paper proposes a tracking method that relies only on depth information, as well as a method of using region growing to identify errors that can occur during the tracking process and a method of detecting the fingertip that can be applied for the recognition of various gestures. First, the closest point of approach is identified through the process of transferring the center point in order to locate the tracking point, and the region is grown from that point to detect the hand region and boundary line. Next, the ratio of the invalid boundary, obtained by means of region growing, is used to calculate the validity of the tracking region and thereby judge whether the tracking is normal. If tracking is normal, the contour line is extracted from the detected hand region and the curvature and RANSAC and Convex-Hull are used to detect the fingertip. Lastly, quantitative and qualitative analyses are performed to verify the performance in various situations and prove the efficiency of the proposed algorithm for tracking and detecting the fingertip.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.50 no.3
• /
• pp.102-112
• /
• 2013

In this paper, two step processing method of contour extraction and complement which contain hexagonal shape for low contrast and noisy images is proposed. This method is based on the combination of Laplacian-Gaussian filter and an idea of filters which are dependent on the shape. At the first step, an algorithm which has six masks as its extractors to extract the hexagonal edges especially in the corners is used. Here, two tricorn filters are used to detect the tricorn joints of hexagons and other four masks are used to enhance the line segments of hexagonal edges. As a natural image, a corneal endothelial cell image which usually has regular hexagonal form is selected. The edge extraction of hexagonal shapes in corneal endothelial cell is important for clinical diagnosis. The proposed algorithm and other conventional methods are applied to noisy hexagonal images to evaluate each efficiency. As a result, this proposed algorithm shows a robustness against noises and better detection ability in the aspects of the output signal to noise ratio, the edge coincidence ratio and the extraction accuracy factor as compared with other conventional methods. At the second step, the lacking part of the thinned image by an energy minimum algorithm is complemented, and then the area and distribution of cells which give necessary information for medical diagnosis are computed.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.18 no.7
• /
• pp.970-979
• /
• 1993

In this paper, a multi-function processor unit is implemented for binary image processing. This unit consists of a set of address generatior, window pipeline register, look up table, control unit, and two local memories .The merits of multi-function processor unit are more simpler than basic SAP and improved disposal speed. A simple software selection give the various choices of image sizes and it can process the function of smoothing, thinning, feature extraction, and edge detection, selectively or sequentially.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.32B no.10
• /
• pp.1294-1304
• /
• 1995

In this paper, a method has been proposed for the fully automatic detection of left ventricular endocardial boundary in B-mode short axis echocardiography without manual intervention by human operator. The proposed method makes use of the weighted model that approximates to endocardium and incomplete edge information for echocardiography. Therefore, this method is more effective than boundary detection by only edge information. The implementation of this method is as follows. First, the proposed algorithms are used in order to detect the approximate boundary, then a weighted model with the approximate boundary is constructed. Finally, the cavity center of the left ventricle performing the Hough transform with the weighted model and edge image can be found automatically, and then the endocardial boundary using detected center, original image, weighted model, and edge image can be detected. validations of this method with experimental results on echo image of dog's heart and clinical echocardiography is verified.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.28 no.6
• /
• pp.867-875
• /
• 2004

In order to inspect burr geometry and hole quality in micro-drilling processes, a cost-effective method using an image processing and shape from focus (SFF) methods on the machine tool is proposed. A CCD camera with a zoom lens and a novel illumination unit is used in this paper. Since the on-machine vision unit is incorporated with the CNC function of the machine tool, direct measurement and condition monitoring of micro-drilling processes are conducted between drilling processes on the machine tool. Stainless steel and hardened tool steel are used as specimens, as well as twist drills made of carbide are used in experiments. Validity of the developed system is confirmed through experiments.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.34S no.5
• /
• pp.35-44
• /
• 1997

In this paper, a an algorithm that detects the endocardial boundary, expanding the region from endocardial cavity using fuzzy inference, is proposed. This algorithm decides the ventricular cavity by fuzzy inference in process of searching each pixel from the inside of left ventricle in echocardial image and expands it. Uncertainty and fuzziness exists in decision of endocardial boundary. Therefore, we convert the lingustic representation of mean, standard deviation, and threshold value that are characteristic variables of endocardial boundary to fuzzy input and output variables. And, we extract proposed method is robuster to noise than radial searching method that is highly dependent on center position. To prove the similarity of detected boundary by fuzzy nference, we used the measures of SIZE, correlation coefficient, MSD, and RMSE and had acquired reasonable results.

• Proceedings of the KAIS Fall Conference
• /
• 2009.12a
• /
• pp.605-607
• /
• 2009

본 논문은 감시 시스템의 객체 추적 시, 정확한 객체 추출을 위해 블록 기반으로 객체를 추적하는 방법을 제안한다. 객체 움직임 추적은 주어진 환경에 따라 변수가 많고, 변수를 대처하는 알고리즘을 많이 추가 할 경우 실시간 추적에 어려움이 발생한다. 특히 배경이 조명이나 바람 등의 환경적 요인에 의해 변화되는 문제는 객체를 추적하는데 가장 큰 문제점이다. 특히 사람이나 멧돼지의 경우 움직임에 의한 객체 구성 요소의 흔들림에 의해 고정 블록의 연산에 의해 움직임 객체를 추적할 때 정확한 객체의 윤곽선을 검출하기 힘들다. 따라서 연속되는 프레임에서 전체 화면의 차영상을 이용하여 움직임 관심 영역을 설정하고, 관심 영역에 해당하는 블록들을 분석하였다. 이를 기반으로 움직임 객체의 최외곽 사각형의 객체 영역을 추출하여 기존 고정 블록 방법에 의한 객체 추적보다 좀 더 정확하게 객체를 추출하고 추적할 수 있다.

• Journal of Korea Multimedia Society
• /
• v.18 no.10
• /
• pp.1149-1156
• /
• 2015

This paper proposes the hand contour detector which is robust to noises. Existing methods reduce noises by applying morphology to extracted edges, detect finger tips by using the center of hands, or exploit the intersection of curves from hand area candidates based on J-value segmentation(JSEG). However, these approaches are so vulnerable to noises that are prone to detect non-hand parts. We propose the noise tolerant hand contour detection method in which non-skin area noises are removed by applying skin area detection, contour detection, and a threshold value. By using the implemented system, we observed that the system was successfully able to detect hand contours.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2018.05a
• /
• pp.137-138
• /
• 2018

이미지의 픽셀 기반 처리는 한 픽셀의 값을 변환하고 다른 픽셀의 값에 관계없이 현재 픽셀의 값에 따라 변환하는 프로세스를 의미한다. 픽셀 기반 처리는 이미지 변환, 이미지 향상 및 이미지 합성과 같은 많은 분야에서 가장 기본적인 작업이다. 본 논문에서는 히스토그램 연산과 같은 영상의 전처리 과정이 경계 검출 결과에 미치는 상호 연관성에 대해 알아보고 픽셀 기반의 처리를 이용하여 효과적으로 영상의 윤곽을 찾는 방법을 제안한다.